Computerized technical authentication and grading system for collectible objects

ABSTRACT

The disclosure described herein is directed to a computerized system and method of grading and authenticating collectibles utilizing digital imaging devices and processes to provide an objective, standardized, consistent high-resolution grading of collectible objects, such as but not limited to sport and non-sport trading cards. The disclosure eliminates the subjectivity present in the human grading process and overcomes the inherent limitations of the human eye.

RELATED APPLICATIONS

This application is a continuation application of Ser. No. 15/964,546 toStephen Kass et al., filed on Apr. 27, 2018, which is a continuationapplication of Ser. No. 15/706,543 to Stephen Kass et al., filed on Sep.15, 2017, now U.S. Pat. No. 10,146,841, which is a continuationapplication of Ser. No. 15/000,989 to Stephen Kass et al., filed on Jan.19, 2016, now U.S. Pat. No. 9,767,163, which claims the benefit ofpriority of U.S. Provisional Application Ser. No. 62/104,606 to StephenKass et al., which was filed on Jan. 16, 2015. The contents of Ser. Nos.15/000,989, 15/706,543, 15/964,546, and 62/104,606, including theirdrawings, schematics, diagrams, and written description, are herebyincorporated in their entirety by reference.

BACKGROUND Field

This disclosure generally relates to a grading and authenticating systemand method of using the same. More particularly, the disclosure relatesto a computerized system for grading and authenticating sport andnon-sport card collectibles and other printed objects including eventticket, programs, photographs and the like.

Description of the Related Art

Card collecting, including sport and non-sport cards, has become, formany fans, much more than a hobby. There is a great deal of potentialvalue in building a card collection and it could take years of research,time, and work. When a collector is interested in building a valuablecard collection, it is very important for the collector to know that thecondition of the card significantly affects its the value as acollectible. As such, it is very common for cards, as well as othercollectible objects, to be professionally evaluated by industryrecognized experts and graded in an effort to determine the value of aparticular card or object. A professionally graded card is inspected forauthenticity and rated on various criteria, for its condition. The cardis then assigned an overall grade, generally from 1-10, sealed in atamper-proof holder (slab) and assigned a certification number that ismaintained by the grading company. A graded card can increase the valueof the card in comparison to an ungraded card of equal or similarcondition by means of offering the card owner or buyer an assurance ofthe card's authenticity and condition.

Grading cards is based on various characteristics that pertain to the“general eye appeal” of the card. Characteristics of the card that areuniversally examined in the grading process are centering, corners,edges, and surface. Centering is the placement of the image (top tobottom and left to right) on the card relative to the card borders.Industry standards exist for percentage of off centering variancepermitted for each of the possible card grades. The corners of the cardare inspected to determine the quality of the physical condition of thecorner and/or if any defect of the corners is present. The edges of thecard are examined, similarly as the corners, to determine the quality ofthe physical condition of the edges of the card, and account for anydamages and/or imperfections along the edges. The surface of the card isexamined to account for any damage and/or imperfections on the card,such as scratches, creases, tears, pinholes, stains, dents, attempts atrecoloring, etc.

Today there are three industry accepted grading companies that representapproximately 99% of the market. Each of the grading companies gradecards by human evaluation, primarily with the naked eye and typicallydevote approximately one minute per card during the grading process.Because this grading process can be highly subjective, it results incards rarely receiving the same grade when graded by any of the threeindustry leaders, or the same grade when re-graded with the same gradingcompany that previously graded the card. As such, there is no gradingmethodology available in the marketplace today that provides accurateand consistent results in cards as well as other collectibles, e.g.,coins, stamps, etc.

Grading is, with extremely rare exception, the most significantdetermination of value, such fluctuations in grading often result inmisstatement of value and lack of confidence in the marketplacenecessary to sustain a stable and efficient market. All of the gradingcompanies solicit resubmission of any previously graded card in itsoriginal holder (slab) by other companies or even graded by themselvesfor the possibility of a higher grade.

Awareness in the marketplace of the possibilities for resubmitted cardsreceiving higher grades has resulted in card owners breaking open the“tamper proof” holders and resubmitting the cards multiple times, ifnecessary, without disclosing that the card has been previously graded.

The variance in grades for resubmitted cards combined with thesubjective and inconsistent card grading process itself results increating a lack of confidence in the marketplace necessary to sustain astable and efficient market.

The present process utilized in the grading industry creates opportunityfor larger collectors (e.g. larger customers of the card gradingcompanies) to manipulate the current system's subjective grading totheir advantage by re-submitting cards for a higher grade based uponnatural human variability or their influence as a large customer. Smallcollectors lack sufficient size to “influence” card grading and oftensell cards at lower prices due to the lower grades they receive.

Without an accurate and consistent grading system in place, there are nomeans of preventing grading companies and/or their larger customers fromexploiting grading subjectivity and doing so at the expense of the smallcard buyer and seller. The “small” card buyer represents theoverwhelming majority of card ownership but disproportionate minority ofownership of card value. This small collector is an entry-levelhobbyist, for example, a young child who buys cards of his “hero” beforethe youngster becomes a collector.

The collectible market's dysfunction is facilitated by a lack ofapplying modern visual technology and computer processing capabilities.Grading today (by hand and by eye) while traditional, is unfair,inconsistent, and has high labor content, relative to the disclosure,which is directed to a computerized grading and authentication systemand method.

The disclosure is a computerized system and method for objectivelygrading and authenticating collectibles. The disclosure is configured toobjectively grade and authenticate collectibles at a higher reliabilityand consistency, by using a finer resolution than is possible with thehuman eye. The present disclosure addresses these needs and providesfurther related advantages.

SUMMARY

The disclosure provides various aspects of a computerized system andmethod for grading and authenticating collectibles, wherein thecondition and quality of an image and the material upon which that imageis placed, is a component of value as determined by the market. Thedisclosure provides a computerized system and method to objectivelygrade and authenticate collectibles. The disclosure eliminates thesubjectivity present in the human grading process and overcomes theinherent limitations of the human eye.

In one aspect of the disclosure, as broadly described herein, acomputerized system is disclosed that grades and authenticatescollectibles, comprising an image acquisition device and a computersystem. The image acquisition device comprises a housing defining aninternal space, an imaging device, at least one light source toilluminate at least part of the internal space, and a stage, wherein thestage is within the housing and receives a collectible. The computersystem comprises at least one processor, and at least one output device,wherein the image acquisition device is configured to receive an inputsignal from the computer system. The image acquisition device isconfigured to transmit at least one output signal to the computersystem. The at least one processor applies at least one image processingroutine to the at least one output signal received from the imageacquisition device such that the at least one processor produces gradinginformation and transmits the grading information to the at least oneoutput device.

In another aspect of the disclosure, as broadly described herein, amethod for grading and authenticating collectibles comprising, capturingat least one image of a collectible, transmitting the at least one imageto at least one processor, applying at least one image processingroutine to the at least one image, producing grading information basedon results of the at least one image processing routine, andtransmitting the grading information to at least one output device.

This has outlined, rather broadly, the features and technical advantagesof the disclosure in order that the detailed description that followsmay be better understood. Additional features and advantages of thedisclosure will be described below. It should be appreciated by thoseskilled in the art that this disclosure may be readily utilized as abasis for modifying or designing other structures for carrying out thesame purposes of the present disclosure. It should also be realized bythose skilled in the art that such equivalent constructions do notdepart from the teachings of the disclosure as set forth in the appendedclaims. The novel features, which are believed to be characteristic ofthe disclosure, both as to its organization and method of operation,together with further objects and advantages, will be better understoodfrom the following description when considered in connection with theaccompanying figures. It is to be expressly understood, however, thateach of the figures is provided for the purpose of illustration anddescription only and is not intended as a definition of the limits ofthe present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of a computerized system according to an aspect ofthe disclosure.

FIG. 2 is a perspective view of an image acquisition device according toan aspect of the disclosure.

FIG. 3 is a view of part a grade report from the computerized systemsaccording to an aspect of the disclosure.

FIG. 4 is a view of corner grading scores of the grade report from thecomputerized systems according to an aspect of the disclosure.

FIG. 5 is a partial view of a collectible and a partial view of cornergrading scores of the grade report from the computerized systemsaccording to an aspect of the disclosure.

FIG. 6 is a partial view of a collectible and a partial view of cornergrading scores of the grade report from the computerized systemsaccording to an aspect of the disclosure.

FIG. 7 is a view of a collectible and a partial view of centeringgrading scores of the grade report from the computerized systemsaccording to an aspect of the disclosure.

FIG. 8 is a view of a collectible and a partial view of centeringgrading scores of the grade report from the computerized systemsaccording to an aspect of the disclosure.

FIG. 9 is a view of a collectible and a partial view of edge gradingscores of the grade report from the computerized systems according to anaspect of the disclosure.

FIG. 10 is a partial view of a bottom edge of a collectible and apartial view of edge grading scores of the grade report from thecomputerized systems according to an aspect of the disclosure.

FIG. 11 is a partial view of a top edge of a collectible and a partialview of edge grading scores of the grade report from the computerizedsystems according to an aspect of the disclosure.

FIG. 12A is a view of a collectible and a partial view of edge gradingscores of the grade report from the computerized systems according to anaspect of the disclosure.

FIG. 12B is another partial view of edge grading scores of thecollectible of FIG. 12A.

FIG. 13 is a view of a collectible and a partial view of edge gradingscores and corner grading scores of the grade report from thecomputerized systems according to an aspect of the disclosure.

FIG. 14 is a partial view of a collectible and a partial view of surfacegrading scores of the grade report from the computerized systemsaccording to an aspect of the disclosure.

FIG. 15A is a view of a collectible and a partial view of corner gradingscores and surface grading scores of the grade report from thecomputerized systems according to an aspect of the disclosure.

FIG. 15B is a partial view of the collectible of FIG. 15A.

FIG. 16A is a view a collectible and a partial view of surface gradingof the grade report from the computerized systems according to an aspectof the disclosure.

FIG. 16B is a partial view of surface grading of the collectible of FIG.16A.

FIG. 17 is a diagram of a computerized system according to an aspect ofthe disclosure.

DETAILED DESCRIPTION

The disclosure described herein is directed to different aspects of acomputerized system and method for grading and authenticatingcollectibles, such as but not limited to sports cards, non-sports cards,coins, stamps, photographs, autographs and the like. The detaileddescription set forth below, in connection with the appended drawings,is intended as a description of various configurations and is notintended to represent the only configurations in which the conceptsdescribed herein may be practiced. The detailed description includesspecific details for the purpose of providing a thorough understandingof the various concepts. It will be apparent, however, to those skilledin the art that these concepts may be practiced without these specificdetails. In some instances, well-known structures and components areshown in block diagram form in order to avoid obscuring such concepts.As described herein, the use of the term “and/or” is intended torepresent an “inclusive OR”, and the use of the term “or” is intended torepresent an “exclusive OR”.

The disclosure uses an image acquisition device that can acquire one ormore high resolution images of a collectible with detail that is at ahigher resolution than that of the naked eye. The high resolution imagesof the collectible provide an enhanced degree of detailing of thecollectible than is possible with the naked eye. The image acquisitiondevice can also be configured to examine the physical condition and/orcharacteristics of the collectible to determine if the collectible hasbeen altered and/or modified. The one or more high resolution images areprocessed using one or more image processing routines for the purpose ofgathering all data applicable to making a determination of theauthenticity, condition and grading of the collectible. Through theapplication of image processing, an analysis and evaluation of specificcriteria can be provided resulting in a more consistent, repeatable, andobjective grade for collectibles being established.

The disclosure can be utilized to obtain detailed information about thecollectible that is not done currently with conventional human gradingsystems. For example, the detailed information obtained allows thedisclosure to quantify the amount of any damage present in thecollectible, if the collectible has been altered from its originalcondition, or if the collectible has been modified in an attempt torepair and/or conceal defects. These alterations and/or modificationscan be imperceptible to the human eye and can result in the human graderassigning an inaccurate grade to the collectible, which therebyimproperly inflates the value of the collectible. Furthermore, althoughit may be possible for the human grader to identify the presence of anydamage in the collectible, the human grader cannot quantify the amountof such damage present in the collectible nor evaluate with a consistentstandard from grading company to grading company, individual grader toindividual grader, or card to card. Conventional human grading systemsare outdated, inaccurate and distort the values of the collectiblemarket.

Additionally, the lack of sophisticated grading systems creates theopportunity for the counterfeiting of collectibles. Counterfeiting isvery prevalent in the collectibles marketplace and the disclosure canassist in detecting and thereby minimizing or even eliminatingcounterfeiting and/or fraud in the collectibles marketplace due, inpart, to the elimination of the human element in the grading process.

Counterfeit cards can be fabricated in modern times that attempt to passfor originals. The quality of counterfeit cards has increased over timesuch that only a trained expert can identify a counterfeit. Thesetrained experts are usually able to tell the difference of a counterfeitand an original. However, sometimes the counterfeit card is in thetamper-proof holder or slab and complete unobstructed access to the cardis limited by the tamper-proof holder. In such instances, the trainedexpert may not be able to determine whether the card is a counterfeit ororiginal. The disclosure utilizing high resolution images of the cardwithin the tamper-proof holder can determine whether the card iscounterfeit through the application of image processing and acomparative analysis of known genuine cards with a card beingauthenticated and graded by application of proprietary algorithms of thedisclosure.

The disclosure is described herein with reference to certain aspects,but it is understood that the disclosure can be embodied in manydifferent forms and should not be construed as limited to the aspectsset forth herein. In particular, the disclosure is described herein inregards to a computerized system and method for grading andauthenticating collectibles, but it is understood that the disclosurecan evaluate and/or examine non-collectible items wherein authenticityand/or legitimacy of a non-collectible item is desired.

Although the terms first, second, etc. may be used herein to describevarious elements or components, these elements or components should notbe limited by these terms. These terms are only used to distinguish oneelement or component from another. Thus, a first element discussedherein could be termed a second element without departing from theteachings of the present application. It is understood that actualsystems or fixtures embodying the disclosure can be arranged in manydifferent ways with many more features and elements beyond what is shownin the figures.

It is to be understood that when an element or component is referred toas being “on” another element or component, it can be directly on theother element or intervening elements may also be present. Furthermore,relative terms such as “between”, “within”, “below”, and similar terms,may be used herein to describe a relationship of one element orcomponent to another. It is understood that these terms are intended toencompass different orientations of the disclosure in addition to theorientation depicted in the figures.

Aspects of the disclosure are described herein with reference toillustrations that are schematic illustrations. As such, the actualthickness of elements can be different, and variations from the shapesof the illustrations as a result, for example, of manufacturingtechniques and/or tolerances are expected. Thus, the elementsillustrated in the figures are schematic in nature and their shapes arenot intended to illustrate the precise shape of a region of a device andare not intended to limit the scope of the disclosure.

FIG. 1 shows one aspect of a computerized system 100 according to thedisclosure.

The computerized system 100 comprises an image acquisition device 102and a computer system 104. The image acquisition device 102 comprises animaging device 106, a housing 108 defining an internal space 110, astage 112, and at least one light source 114 to illuminate at least partof the internal space 110, wherein the stage 112 is within the housing108 and receives a collectible 116. The computer system 104 comprises atleast one processor 120 comprising processor-executable computerinstructions and at least one output device 122, wherein the computersystem 104 is configured to transmit one or more control signals to theimage acquisition device 102.

The housing 108 comprises a base 109, a top 111, and a plurality ofsidewalls 113, wherein the base 109 and top 111 are coupled to theplurality of sidewalls 113 such that the base 109 is opposite the top111. The base 109, top 111 and plurality of sidewalls 113 define theinternal space 110 of the housing 108.

The stage 112 is disposed within the internal space 110 of the housing108 and provides a support surface 115 to receive the collectible 116.The positioning of the support surface 115 within the housing 108 isadjustable to any height within the internal space 110. In some aspects,the support surface 115 can also be adjusted about one or more axes,such that the support surface 115 can be angled with respect to theimaging device 106, at least one light source 114 or a combinationthereof within the internal space 110.

An imaging device 106 is adapted to capture at least one image of thecollectible 116. The at least one image of the collectible 116 capturedby the imaging device 106 is a high resolution digital image of thecollectible 116. The high resolution digital image is a digitalrepresentation of the collectible 116 and is processed using at leastone image processing routine to determine a grade of the collectible 116based on a set of technical grading criteria. In one aspect, the imagingdevice 106 can be a high resolution digital camera, such as but notlimited to an 18 megapixel digital camera. However, the imaging device106 is not intended to be limited to an 18 megapixel digital camera, andcould have a resolution that is higher or lower than 18 megapixels. Inaddition, the imaging device 106 is not intended to be limited to adigital camera. When the imaging device used is a camera, the camerawithin the housing 108 is adjustable to any height within the internalspace 110 to increase or decrease field of vision. In other aspects, theimaging device 106 can be a scanner or other imaging device that cancreate a digital image or other reproduction of the collectible 116.

In aspects wherein the imaging device is a scanner, the scanner can bephysically isolated from or replace and/or supplement the housing 108and can have its own self-contained stage 112, internal space 110, atleast one light source 114, and a sensor to capture the image of thecollectible on the surface. Such a scanner device is intended to beunderstood as an alternative or supplement in any description of thesystem herein. One example of a scanner can be a flatbed scanner.However, the scanner, or multiple scanners, can be arranged in manydifferent known configurations, and is not intended to be limited to aflatbed-like scanner.

In aspects that utilize a digital camera as the imaging device, thecollectible 116 is arranged on the surface 115 of the stage 112, suchthat the collectible fills approximately 90% of the camera's field ofview. With an 18 megapixel digital camera, for example, this results inapproximately 1200 pixels of resolution per inch of a typical 3.5″×2.5″collectible card. A higher resolution camera would, in turn, yield ahigher-resolution image. In other aspects, the collectible can bearranged to fill more or less than the camera's field of view and is notintended to be limited to 90%. This above 1200 pixels per inch is anexample of what could be considered high resolution for any imagingdevice 106 of the image acquisition device 102, and is not intended tobe limited to aspects that utilize a digital camera. The above alsoapplies to other imaging devices, such as but not limited to a scanner.The imaging device 106 can obtain an image of the collectible 116 invarying pixels of resolution per inch. For example, the pixels ofresolution per inch can start from at least 300 pixels per inch andincrease as desired. However, this example is not intended to be abaseline that needs to be met in order to qualify as high resolution.Images having 300 pixels per inch is generally accepted in digitalphotography as being high resolution images.

In one aspect, as shown in FIG. 1, the imaging device or camera 106 ison the top 111 of the housing 108 and is positioned to face thecollectible 116 on the support surface 115, wherein the support surface115 is proximate the bottom 109 of the housing 108. The imaging device106 can be removably coupled to the top 111, while in other aspects, theimaging device 106 can be disposed on the top 111. The housing 108 isconfigured to accommodate the imaging device 106 to allow the imagingdevice 106 to capture the at least one image of the collectible 116.

For example, in the aspect of FIG. 1, the top 111 of the housing 108comprises an opening (not shown) that provides access to the internalspace 110 of the housing 108 which allows the imaging device 106 to beon the housing 108, external to the internal space 110. The imagingdevice 106 is aligned with the opening of the top 111 in order tocapture the at least one image of the collectible 116. The imagingdevice 106 can comprise physical dimensions that are greater than theopening of the top 111 such that the imaging device 106 can be onportions of the top 111 beyond the opening.

However, in other aspects, the imaging device 106 can comprise physicaldimensions that are less than or similar to the opening of the top 111.The imaging device 106 can be configured to be externally disposed withrespect to the internal space 110 of the housing 108 in order to capturethe at least one image of the collectible 116. In other aspects, part ofthe imaging device 106, for example a lens body, at least partiallyextends into the internal space 110 of the housing 108 in order tocapture the at least one image of the collectible 116.

The housing 108 is configured to block penetration of exterior lightinto the internal space 110, which prevents exterior light from alteringthe lighting condition of the internal space 110. It is important toprevent and/or limit exterior light from entering the internal space 110because exterior light could impinge on the collectible 116 and/or alterthe pre-defined lighting condition, which could affect the accuracy ofthe grading of the collectible 116. At least one advantage of thedisclosure is that the grading of a collectible is repeatable with veryaccurate and consistent results. This is due, in part, to the highresolution images captured by the imaging device 106 under controlledpre-defined lighting conditions. However, in other aspects, exteriorlight may enter the internal space 110 of the housing 108 such thatimages captured by the imaging device 106 in the presence of exteriorand/or uncontrolled light are acceptable for grading.

The housing 108 further comprises at least one light source 114 toilluminate at least part of the internal space 110. The at least onelight source 114 can be configured to provide a plurality of differentlighting conditions, wherein the imaging device 106 captures an image ofthe collectible 116 under each of the different lighting conditions. Theplurality of different lighting conditions accentuate the physicalcondition of the collectible 116 in order to detect defects and/orimperfections. For example, an indentation, scratch or crease on thecollectible can cause a shadow under certain lighting conditions and theshadow can be examined to determine the extent of the indentation,scratch or crease. This is an example of the lighting conditionsassisting in identifying a defect, and neither the invention nor thedefects identified are intended to be limited to such examples.

The at least one light source 114 is positioned within the internalspace 110 in order to provide the different lighting conditions. In theaspect of FIG. 1, the housing 108 comprises a plurality of light sources114 that are mounted to the sidewalls 113 and the top 111 (shown inphantom). The light sources 114 are positioned within the housing 108with respect to the collectible 116 on the support surface 115 and areconfigured to emit light in response to a control signal transmittedfrom the computer system 104. The control signal from the computersystem 104 controls the on/off state of each of the light sources 114 inorder to provide the different lighting conditions, wherein each of theplurality of different lighting conditions is a pre-defined lightingcondition. The pre-defined lighting conditions allow collectibles 116 tobe illuminated under the same set of lighting conditions that areconstant and repeatable. Different pre-defined lighting conditions canbe set for different types of collectibles. For example, the pre-definedlighting conditions for a baseball card may vary from the pre-definedlighting conditions of a stamp or coin.

In yet other aspects, as shown in FIG. 2, the imaging device 106 can bewithin the internal space 110 of the housing 108.

For the same or similar elements or features, the same reference numberswill be used throughout the application herein. In the aspect of FIG. 2,the housing 108 comprises a support structure 202 interposed between thebase 109 and the top 111 to receive the imaging device 106. The supportstructure 202 provides support to the imaging device 106 such that theimaging device 106 is substantially stationary within the internal space110. The imaging device 106 is substantially stabilized within thehousing 108 in order to capture the at least one image of thecollectible 116. The positioning of the support structure 202 can beadjusted to any height within the housing 108. This allows theseparation between the collectible 116 and support structure 202 to bevaried as desired. In other aspects, the support structure 202 can alsobe adjusted about one or more axes, such that the support structure 202can be angled within the internal space 110.

The light sources 114 can comprise many different types of lightsources, such as but not limited to, incandescent, fluorescent, lightemitting diodes (LED), and the like, or a combination thereof. In theaspects of FIGS. 1 and 2, the light sources 114 can comprise LED lightstrips that are electrically connected in either series or parallel. Atleast one advantage of using LEDs as a light source is that LEDs providetruer color information to the imaging device 106. The LED light stripsare connected to the computer system 104 and emit light in response tothe control signal from the computer system 104. In one aspect, the LEDlight strips are individually connected to the computer system 104 andhave a dedicated control signal connection. This allows for betterlighting control due in part to LEDs being more exact in terms of lightemission. While in other aspects, the LED light strips are connected tothe computer system 104 using a shared control signal connection.

The housing 108 can comprise many different materials and/or manydifferent configurations. For example, in the aspect of FIG. 1, the base109, the top 111, and the sidewalls 113 of the housing 108 comprisesolid construction material that substantially blocks exterior light. Inother aspects, as shown in FIG. 2, the housing 108 comprises ametal-wire scaffolding. The housing 108 of FIG. 2 does not, by itself,substantially block exterior light, and therefore further comprises acover 204 that covers the housing 108. The cover 204 can be a blackoutcurtain known in the art that are used to block light, or can be anyother material, device or structure that blocks out exterior light. Thecover 204 can also be used with the housing 108 of the aspect of FIG. 1in an effort to further ensure that substantially all exterior light isblocked out and does not enter the housing 108. Exterior light enteringthe internal space 110 could alter the lighting condition within theinternal space that could result in an erroneous grading of thecollectible. In other aspects, the housing 108 can comprise an accesspanel or other means for accessing the internal space 110, such as butnot limited to a hinged sidewall or part of a sidewall being hinged.

The disclosure is not intended to be limited to the configuration and/orthe number of light sources 114 disclosed in the aspects of FIGS. 1 and2. The light sources 114 can be arranged in many differentconfigurations within the housing 108, and can comprise the same ordifferent amount of light sources 114. For example, in other aspects,the light sources 114 can only be on one or more sidewalls 113, whereasin other aspects the light sources 114 can only be on the top.

The computer system 104 comprises at least one processor 120 and atleast one output device 122, wherein the computer system 104 isconfigured to transmit one or more control signals to the imageacquisition device 102. The one or more control signals provideinstructions to each of the at least one light source 114 and theimaging device 106. The computer system 104 transmits instructions viathe control signal to the at least one light source 114 such that the atleast one light source 114 provides a desired lighting condition inaccordance with the instructions. The computer system 104 can also senda control signal to the imaging device 106 with instructions to capturean image of the collectible 116 after the at least one light source 114is illuminating the collectible 116 under the desired lightingcondition. The image acquisition device 102 thereby transmits an outputsignal to the computer system 104, wherein the output signal comprisesthe captured image of the collectible. In one aspect, the imageacquisition device 102 can transmit the output signal to the computersystem along the same connection that the image acquisition device 102received the control signal from the computer system 104, while in otheraspects, the output signal is transmitted from the image acquisitiondevice 102 to the computer system 104 along a different connection. Theconnections between the image acquisition device 102 and the computersystem 104 can be wired connections, wireless connections, or acombination thereof.

The computer system 104 can be configured to run a script comprising aseries of instructions for the imaging device 106 and the light sources114. For example, in one aspect, the script can comprise a sequence ofactions wherein a series of control signals are transmitted to theimaging device or digital camera 106 and the light sources 114 such thatthe on/off state of one or more of the light sources 114 isactivated/deactivated to provide one of a series of pre-defined lightingconditions, wherein the imaging device or digital camera 106 captures animage of the collectible 116 illuminated, if needed, in each one of theseries of pre-defined lighting conditions, such that after each image iscaptured, the imaging device 106 transmits the captured image to thecomputer system 104, and the computer system 104 labels the image usingmetadata, exchangeable image file format (exif), and the like, and/or bynaming the image filename to indicate the lighting condition under whichthe image was taken. This process repeats until an image has beencaptured under each of the series of pre-defined lighting conditions.The collectible 116 is stationary on the surface 115 and its positioningis not altered while the series of instructions are implemented by thelight sources 114 and the imaging device 106. This results in each ofthe captured images being substantially aligned while illuminated underthe different lighting conditions.

In one aspect, there can be nine different lighting conditions in whichan image of the collectible 116 is to be captured. This will result in aset of seven to nine images of the collectible 116 in the seven to ninedifferent lighting conditions. These images will then be processed andanalyzed by the computer system 104 to determine a grade for thecollectible 116. The disclosure is not intended to be limited to onlyseven to nine different lighting conditions. The disclosure can comprisemore or less than seven to nine light different lighting conditionsresulting in any number of images of the collectible.

In some aspects, the different lighting conditions can be provided byactivating one of the light sources 114 and deactivating the remaininglight sources 114, and repeats until each of the light sources has beenactivated individually. The number of captured images of the collectible116 in different lighting conditions can be proportional to the numberof light sources 114, or can be independent of the number of lightsources 114. In other aspects, the different lighting conditions can beprovided by activating a plurality of the light sources 114 anddeactivating the remaining light sources 114. In such aspects, theintensity of light emission of the plurality of light sources 114 thatare activated can be equivalent or different.

After the series of instructions has been completed, the collectible 116can be repositioned, either automatically or manually, in order tocapture images of another side of the collectible 116 utilizing the sameand/or different series of instructions. For example, a collectible 116,such as but not limited to a baseball card, has a front side and a backside, such that when all the images of the front side have beencaptured, the baseball card can be automatically or manually turned overon the surface 115 to capture images of the back side. The lightingconditions for the back side of the card can be the same or differentthan the front side. For example, one side of the card can be glossywhile the other side is not, such that different lighting conditions maybe needed to give a proper grade. In one aspect, images of both thefront and back sides of the baseball card under the different lightingconditions can be taken for the purpose of grading the baseball card.However, in other aspects, images of only one side of the baseball cardcan be taken for the purpose of grading the baseball card. In yet otheraspects, the collectible 116 can comprise a plurality of sides, whereinimages of each of the plurality of sides can be captured in thedifferent lighting conditions for the purpose of grading the collectible116. However, in other aspects, images of at least one of the pluralityof sides can be captured in the different lighting conditions for thepurpose of grading the collectible 116. The collectible 116 can berepositioned manually to expose another side, while in other aspects,the repositioning of the collectible 116 could be automated. In yetother aspects, the image acquisition device 102 can comprise a pluralityof imaging devices 106, such that the image acquisition device 102 cancapture images of the top and bottom sides of the collectible 116simultaneously, or without having to turn over the collectible tocapture images of another side of the collectible. In such aspects, thecollectible 116 can be interposed between the plurality of imagingdevices 106.

Upon completion of the series of instructions, the computer system 104will have a single or a plurality of images of the collectible 116,wherein each image is a high resolution image of at least a portion ofthe entire surface of the collectible 116 illuminated in a differentlighting condition. Each image are labeled by the computer system 104 toidentify the lighting condition it was taken. The images can be storedon an internal storage device of the computer system 104 or can bestored on an external storage device that is accessible by the computersystem 104. The images will then be processed and analyzed under one ormore image processing routines. In one aspect, after the computer system104 receives the images from the image acquisition device 102, or froman image source external to the image acquisition device, the computersystem 104 applies at least one image processing routine wherein theimages are substantially aligned such that all the images are insubstantially the same orientation and/or dimensions as each image inthe database and with each future image created for grading. This allowsfor images to be overlaid and assist in the image processing. In someaspects, the system 100 comprises one or more collectible image sourcesand creates and stores one or more images of the respective collectible116, wherein multiple collectibles 116 can be graded concurrently fromeach image source. For example, the system 100 can comprise a pluralityof image acquisition devices 102 and/or configured to receive at leastone external signal comprising an image of a collectible. This allowsthe system 100 to grade multiple collectibles 116 and operate in anefficient manner.

For a firmware and/or software implementation, the methodologies may beimplemented with modules (e.g., procedures, functions, routines and soon) that perform the functions described herein. A machine-readablemedium tangibly embodying instructions may be used in implementing themethodologies described herein. For example, software codes may bestored in a memory and executed by a processor unit. Memory may beimplemented within the processor unit or external to the processor unit.As used herein, the term “memory” refers to types of long term, shortterm, volatile, nonvolatile, or other memory and is not to be limited toa particular type of memory or number of memories, or type of media uponwhich memory is stored.

If implemented in firmware and/or software, the functions may be storedas one or more instructions or code on a computer-readable medium.Examples include computer-readable media encoded with a data structureand computer-readable media encoded with a computer program.Computer-readable media includes physical computer storage media. Astorage medium may be an available medium that can be accessed by acomputer. By way of example, and not limitation, such computer-readablemedia can include RAM, ROM, EEPROM, CD-ROM or other optical diskstorage, magnetic disk storage, solid state or other magnetic storagedevices, or other medium that can be used to store desired program codein the form of instructions or data structures and that can be accessedby a computer; disk and disc, as used herein, includes compact disc(CD), laser disc, optical disc, digital versatile disc (DVD), floppydisk and Blu-ray disc where disks usually reproduce data magnetically,while discs reproduce data optically with lasers. Combinations of theabove should also be included within the scope of computer-readablemedia.

In addition to storage on computer readable medium, instructions and/ordata may be provided as signals on transmission media included in acommunication apparatus. For example, a communication apparatus mayinclude a transceiver having signals indicative of instructions anddata. The instructions and data are configured to cause one or moreprocessors to implement the functions outlined in the claims.

In one aspect, the computerized system 100 is configured to objectivelygrade collectibles 116, such as but not limited to baseball cards,according to a set of technical grading criteria (see listing of Table1). The methodology for detecting defects in a collectible 116 comprisesthe collectible 116 being examined for variations of each criteria withrespect to a perfect reference image or Golden Image stored in adatabase 130.

TABLE 1 Number Category Criteria 1. Overall Subject Eye Appeal ColorCentering Stains Scratching Creasing Printing errors Shape Size ofSubject Length (permitted variance to allow for inexact cutting oldersubjects) Diameter Width (permitted variance to allow for inexactcutting older subjects) Thickness of Consistency (has part or whole ofSubject subject been pressed) Identification Year of set (manufacture)of Subject Name of Manufacturer Player or person name Player or personstatus (R, HOF, error Subject) Subject number Subject owner Subjectregistration number or file number Subject detail grading specifics forpoint reductions Inconsistencies Specific alerts color Specific alertsborders Mis-cut (length and width) 2. Corners Angle, Residual, Fray andFill Hanging fiber Dents Chips Folds Crease Scratches Trimming BleachingAdded material Added Coloring Pressing Moistening Gluing 3. SubjectSurface Gloss Color (including no added color) Borders (including nobleaching or cutting) Misprinting/print defects Mis-cut Creases CracksFolds Chips Scratches Pin holes Tape and other stains Tears Variationsfrom Golden Image Known Counterfeit Defects 4. Centering Front ofsubject: Left/Right Front of subject: Top/Bottom Back of subject:Left/Right Back of subject: Top/Bottom Image skew 5. Subject Back StainsPrint errors Dents Chips Folds Creases Scratches Variations from GoldenImage Pin holes Tape and other stains Tears 6. Edges Cutting razor marksCutting and no hanging fiber Cutting resulting whiteness Cutting andresulting subject dimensions Laser cutting Laser cutting and no hangingfibers Laser cutting resulting subject dimensions Signs of pressingSigns of adding material Signs of bleaching (centering) Signs ofcoloring Gluing Moisture Stretching Shrinking Peaks & Valleys FrayingSanding or filing Pressing Polishing

A Golden image 117 for a collectible 116, i.e., perfect image withoutany unintended defects included by its originator, may be created in thefollowing manners: (1) An image of the collectible 116 in its originalformat (“Original Golden Image”) is supplied by its creator and enteredinto the computerized system 100 and stored in a file (the “ImageLibrary”) in a tangible computer memory medium, such as the database130; (2) a Golden Image is created by altering and enhancing acollectible 116 image (“Virtual Golden Image”) by removing alldetectable defects unintended by its originator through the use of imageprocessing and storing the newly created Virtual Golden image in a“Golden Image Library” in a tangible computer memory medium, forexample, in a data structure, such as the database 130; (3) the highestgraded card graded by the system 100 becomes the de facto Golden imageuntil a higher graded card is found; or (4) by using machine learning,assembling perfect portions of other copies of the same card containedwithin the database. In aspects where the golden image for a collectibleis not available, the system can use the highest graded card as thedefacto golden image. Subsequent grading of similar cards with highergrades can become the new golden image. The system 100 might not knowwhat defects were unintended or get an original image from the creatorto have a golden image. As such the system 100 is configured to create agolden image by using the highest graded card. In other aspects, thesystem 100 can create a golden image by taking portions of differentgraded cards that are highly graded and combine them with other highgraded portions to form a golden image.

Machine learning maps visual features to an overall card grade that isaccurate and consistent beyond what human graders can provide. In oneaspect, a machine-learning algorithm, known as k-nearest neighbors,combines the values of measured attributes into a single score for theportion of the card or collectible being evaluated. In one aspect, the kvalue for the nearest neighbors can be 11, such that the eleven nearestneighbors are used. However, other k values for the nearest neighbor canbe used and the disclosure is not intended to be limited to a value of11 for k. In an example of obtaining a corner score for a card usingmachine learning, the corner algorithm can examine a number ofattributes, such as, for example, 4 attributes, and derive individualcorner scores for each of the four corners. From those four individualcorner scores, the overall card corner score is computed. Thefundamental computation of a single corner score is derived fromindividual corner scores for each of the four corners using aproprietary algorithm to weight the four corner scores to arrive at thesingle corner score. A weighting of the four corner scores may include asmall increase in the minimum value in certain situations, such as, whenthe lowest scored corner is significantly different from the other threecorners, or when the overall card grade will not be above apre-established threshold grade (on a 10 point scale). The increase canbe 0.25 point, but can be set at other values. The result is the overallcard corner score that can be expressed on a 1000 point scale (that is,with a resolution of 1/1000). The card corner score can also beexpressed with the same relative resolution on a 10 point scale. Themachine learning algorithms can be further refined by input from trainedprofessional human graders.

The database 130 comprises a datastore of known collectibles, such asbut not limited to baseball cards. The database 130 comprises as manyimages of collectible as possible, and grows as additional images areadded. The database 130 can also grow as the computerized system 100 isused to grade collectibles. Along with each image, a set of metadata isstored, which can comprise information about the collectible or baseballcard 116, such as but not limited to: manufacturer of the card; year ofthe card's manufacturing; series name of the card; name of player orperson on the card; the card number; any variation particular to thatcard series, e.g. red-black or gray-black; any ownership informationavailable; any distinctive features or other information unique to thatparticular card, e.g., distinctions such as, but not limited to, Hall ofFame, Rookie, traded, high number, limited production, etc.; geometricinformation about where the inner-image appears within the cardstock orvalue-altering variations, e.g., autographs on the card. This set ofmetadata is described in relation to baseball cards, but the metadata isnot intended to be limited to baseball cards. Metadata of other types ofcollectibles can also be collected. The computerized system 100 can beconfigured to allow the addition of any grading-specific informationinto the computer system 104 in order to facilitate faster processing orspecific tasks. For instance, the computer system 104 could receive atest file comprising a set of initial perceptual hashes, which wouldspeed the matching of a newly-imaged collectible or card 116 to theknown cards of the database 130. Alternatively, it might includeinformation about the owner of the currently-imaged card or collectible116, wherein the database 130 options can then be filtered by thatinformation and the best-match of only that owner could be found.

In one aspect, a comparison between the image of the collectible 116 andthe Golden image 117 is conducted by the computer system 104. The imageof the collectible 116 is first obtained and identified, as discussedabove, by the computer system 104, and the Golden image 117corresponding to the collectible 116 is retrieved from the Golden ImageLibrary stored on the database 130. After the Golden image 117 for thecollectible 116 is retrieved, one or more image processing routines areapplied to the image of the collectible 116 for the purpose of gatheringall data applicable to making a determination of the authenticity,condition and grading of the collectible 116. An example of an imageprocessing routine utilized is a card identification algorithm. Thecard-ID algorithm takes as input the image of the collectible or card116 and outputs the identity of the card, if there is a match availablein the database 130. If there is no match, the algorithm issues alert toindicate that this is the first time this specific collectible or card116 has been seen and a prior image does not yet exist in the imagedatabase. In this case, information about the card (manufacturer, etc.)can be manually inputted into the database 130, and that informationalong with the image of the collectible or card 116 will be added to thedatabase 130. The card-ID algorithm distills all of the captured imagesof the collectible or card 116 into the database 130 in 64-bitperceptual hashes, as known in the art.

When the system 104 receives a newly-obtained image of a collectible orcard 116, its 64-bit perceptual hash is also computed. Then, theperceptual hash of the newly-obtained image is compared to all of theknown hashes from the database 130. The top 200 closest matches are thenconsidered, one-by-one, and the collectible's or card's 116 pixels aredirectly compared to the images in the database 130 using a templatematching process, such as but not limited to OpenCV's template-matching.The best of those template-matched images, if within a threshold, isdeclared the correct match or archived, if running in batch mode. Ifnone of the images matches within the threshold, the system 104 declaresthat no match was found. The system 104 is not intended to be limited tocomputing 64-bit perceptual hashes of the images. In some aspects, thesystem 104 can compute perceptual hashes of varying sizes, higher orlower than 64-bit, such as but not limited to, 128-bit, 256-bit, etc. Insome aspects, the system 104 can utilize various hash functions and isnot intended to be limited to perceptual hash functions.

Table 1 identifies various specific criteria that may be examined by theimage processing methods of the disclosure, in any combination, usingsix broad categories of criteria. Through the use of thresholds andalgorithms, collectible 116 data is collected and applied to fourcondensed categories (Front and Back): (1) Corners; (2) Edges; (3)Surface; and (4) Centering. Within each category, as well as for generaleye appeal, many image processing methods/algorithms may be utilized sothat, for example, 72 or more criteria may be evaluated and analyzed foreach collectible 116.

After all the images are collected and processed, 50 separate raw datascores of 1-1,000 are determined for each card—25 for the front side and25 for the back side, thereby giving a total maximum raw card score of50,000. The raw scores can be collected for the front and back asfollows: 16 raw corner scores comprised of scores up to a maximum of1,000 each for Fray, Fill, Residual and Angle (these terms to be definedwithin), thereby a maximum “Raw” score of 4,000 for each of the fourcorners for a total of 16,000 for corners; 4 Centering (defined herein)scores up to a maximum of 1,000 each for—top, bottom, left, right,thereby a maximum total raw score of 4,000 for centering; 4 Edge(defined herein) scores—up to a maximum raw score of 1,000 each for top,bottom, left, right thereby a maximum total raw Edge score of 4,000 foredges; 1 Surface score (defined herein)—combining the data from allsurface defects for maximum raw Surface score of 1,000 for surface. Thisprovides a possible maximum total raw score of 25,000 each for front andback of the card.

The 25 raw scores for front and back are processed by proprietaryalgorithms to arrive at 11 attribute scores, for each of the front andback of the collectible, up to a maximum of 1,000 each for front andback: 4 attribute Corner Scores up to a maximum attribute score of4,000; 2 attribute Centering Scores, for top/bottom and left/right, upto a maximum attribute score of 2,000; 4 attribute Edge Scores, for top,bottom, left and right, up to a maximum attribute score of 4,000; and 1attribute Surface Score up to a maximum attribute score of 1,000. Thisthen provides a possible maximum total attribute score of 11,000 eachfor front and back of the card for a total of 22,000. These scores arethen processed by proprietary algorithms to arrive at a single CardGrade with a maximum possible Card Grade of 1000. The numeric valuesused herein are illustrative but do not limit this disclosure in anyway. This disclosure's algorithms can use scales sufficient to capturethe accuracy and repeatability of the image-processing and final grades.

The computerized system 100 can utilize numerous image processing tools.The underlying image processing technology required for carrying out thevarious aspects of the disclosure and variations thereof is readilyavailable in the art. For example, facial recognition technologyutilizes a “Subject” photo and scans one or more databases (ImageLibraries) to locate the Subject within the Library. In this locatorprocess the purpose is to identify the Subject and to compare theSubject to a Golden Image once retrieved from an image library for thepurpose of establishing a probability of a “match”.

In one aspect, the computerized system 100 measures light diffractionfrom an edge or surface defect and measures peaks and valleys on theedge indicating extrusions or indents on the edge relative to a straightline fitted on the edge or as with surface defects with high precisionmeasurement of the degree (length and area) of light diffusion by numberof pixels or other area measurement. Mixing Red, Green and Blue to formmillions of colors and shades of similar colors creates the colorpalette from which all colors are derived. The computerized system 100may, for example, utilize 256 different reds, 256 different blues and256 different greens (the known color palate) to create the entire colorpalette of 16,777,216 different colors. With the use of highly sensitivelenses and resolution, individual pixels can be measured and any changein color can be identified and measured. Any scratch or blemish may beidentified and measured for length, width, area (in pixels for example)and location on the collectible 116. Light may be directed at thecollectible 116 from above and the computerized system 100 identifiesand measures the increase or decrease in the surface of the collectible116 thus identifying depression in surface, pressing of materials, awave on the surface, and/or altering of the paper stock within thecollectible 116, etc.

Another example of an image processing routine is an image subtraction,wherein all data points on a Golden Image 117 may be utilized toeliminate all identical data points on the front and back of thecollectible 116. The data that remains on the front or back of thecollectible is thereby determined to be one or more defects (a mark orspace not on the Golden Image) in the collectible. Image Subtraction maybe utilized to determine differences in the collectible from the GoldenImage such as but not limited to color (fading, alteration, re-coloringand other alterations; like bleaching of image and/or card, etc.) orscratches, chips, or dents. In similar fashion, image subtraction canalso identify existing stains, added color to fill in areas of defect,printing errors, the effects of bleaching, stain removal, the additionof material (i.e., paper stock) or other material and image removal forthe purpose of altering the width of the collectible's borders in anattempt to re-center the collectible.

FIGS. 16A and 16B illustrate an example of image subtraction. The defectspots 301 on the card of FIG. 16A are all that remain after imagesubtraction, as shown in FIG. 16B. In this manner, the system 100 candetermine the number of defects identified on the collectible ascompared to the Golden Image. The system 100 may also be configured tomeasure the individual defects, measure the cumulative total number ofdefects and/or measure the individual and combined area of the surfacecovered by the defects.

The system 100 can be configured to calculate through the use of variouspixel measurements at high magnification and resolution whether acollectible 116 has been resubmitted for grading by the system 100, andhas either been switched or altered from its initial grading. Anypreviously graded card can be re-graded and can subsequently beauthenticated as the original collectible thus eliminatingcounterfeiting and alteration. The system 100 may be configured to“fingerprint” each collectible using high-resolution imagery. The imagescaptured by the image acquisition device 102 under the differentlighting conditions highlight and uncover the unique physicalcharacteristics and/or defects of each card that is graded by the system100. These characteristics and/or defects are unique to each card andare difficult, if not impossible, to replicate. These images are storedon the database 103 and serve as a fingerprint of the graded card basedon the physical characteristics and/or defects of the card. The system100 may store the high-resolution image in a collectible image file andis able to use the “fingerprint” to authenticate a collectible that isin a holder (“Slab”) or other grading company's holder if thecollectible was put in a slab by another company but graded by thesystem 100. In both instances, the collectible need not be removed fromthe holder (“Slab”) to authenticate it. The system 100 is able to storea high-resolution image of a collectible and create a “fingerprint” ofthe collectible for future authentication purposes of all collectiblesgraded by the system 100 even if the previously graded collectibleremains in its slab. If a person desires, and if the image can becollected under acceptable lighting conditions, it may be possible touse a smart phone camera or other remote digital camera or smart phoneapp or other computerized application to record an image of thecollectible for which authentication is desired. The system 100 may beconfigured to receive a signal external from the image acquisitiondevice 102 comprising at least one image of the collectible to beauthenticated and will identify its stored “fingerprint” image andcompare the corners, borders, centering and edges for fiber, pixel andother measurement data that will confirm, at least preliminarily, if thecollectible is the authentic collectible or a replacement (substitution)of a previously graded collectible or is a counterfeit of thecollectible.

A corner algorithm measures several visual attributes whose combinationwill yield an accurate estimate of the corner score for each of thecard's four corners. The source code serves as the most detaileddefinition of the image attributes, but we describe here the motivatingidea for each:

-   -   a. [angle] A line is fit to each of the corner's perpendicular        edges, and the nearness to a sharp right angle (90 degrees)        produces the corner-shape attribute: the closer to 90 degrees,        the higher the score.    -   b. [residual] This attribute measures how close the edge of the        cardstock comes to the mathematical lines that define the        corner: the closer, the higher the score.    -   c. [fill] The extent to which the cardstock is present        throughout the mathematically-defined corner: the more that is        present, the higher the fill attribute.    -   d. [fray] The attribute measures the fall-off in the cardstock        near the corner: the less fraying there is, and thus the higher        the score.

Through the disclosure's proprietary algorithms, those four individualcorner attribute scores are then calculated to generate a score for eachof the corners and for the four corners as a single corner score of thesubject card.

An edge algorithm measures at least three attributes for each of thefour edges of the card from a certain distance from the corners, such as0.75 inches from the corner. This distance can be adjusted by the system104. Each of these three attributes corresponds may be used to identifydefects on each of the four edges:

-   -   a. [residual] The differences between the actual cardstock edge        and the mathematical line that approximates that edge. The area        of these “peaks and valleys” is measured: the smaller the area,        the higher the value of this residual attribute.    -   b. [fray] The change in the color of the cardstock as it        transitions from the edge toward the interior of the card is        also measured: less change indicates that the margin of the card        is more pristine and carries a higher value for this fray        attribute.    -   c. [color] In addition, the uniformity of the color across the        edge is an important consideration: the more uniform, the better        the value of this color edge attribute.

As with corners, the individual edge-score results from a learnedrelationship among these three attributes, based on knowledge frompreviously graded cards, predetermined perfect 90 degree angles orperfect straight lines, and/or from accepted and quantified industrystandards. Through the disclosure's proprietary algorithms those fourindividual-edge scores, top, bottom, left and right, are then calculatedto generate a score for the edges of the object card.

The outermost vertical and horizontal edges of a card when looked at,from above, at high resolution can show an imperfect edge that may havebeen subject to various points of indentation and/or expansion (peaksand valleys). These edge imperfections may be the result of impropercutting of the edge, alterations of the edge, pressure from rubberbands, pressure from fingers, pressure from storage methodology or acard being impacted or dropped. Under high magnification and resolutionthey are unique and constitute a “fingerprint” for the card. The system100 may be configured to fit a virtual line parallel to the outermostright and left side edges from the top edge of the card to the bottomedge of the card (“Vertical Centering Line” left or right, front orback) or from the left outermost edge of the card to the right outermostedge (“Horizontal Centering Line” top or bottom, front or back).Horizontal Centering Lines and Vertical Centering Lines run parallel tothe outermost edge at the precise location determined by a thresholdcreating a virtual line to be fit through any imperfection, jag, hangingfibers, peaks (expansion), valleys (indents) to meet predeterminedthresholds. Thresholds are fixed/preselected in an algorithm andestablish what portion of an edge is defined as Peaks and what portionis defined as valleys (troughs). In one aspect, the system 100 may useup to five hundred measurement points along each edge to measure thePeaks and valleys to determine the number of each, their location, thearea of each and the area of the surface of the card that is affected.Additionally the system 100 may be configured to determine if the cardoutside edge has been cut or altered. The cut or altered edge has adifferent appearance than that of the other edges or of cards from thesame series and/or set when compared to the “Golden Image.” Thehigh-resolution image would be able to display the inconsistentappearance of the cut or altered edge. This high-resolution image of thepeaks and valleys of the edges contribute (with other uniqueidentifiers) to a “fingerprint” of the card that may be retained in thecard Image File.

Image(s) and/or text are typically printed on the front and back surfaceof a card or collectible 116. The Vertical and Horizontal edges of theimage and/or text on the front and/or back (left, right, top and bottom)of a card when looked at from directly above at high resolution willshow an imperfect edge of the image and/or text as a result of printerror or any aberrations (wandering pixel(s) that stray from the imageduring the printing process). The system 100 may be configured toestablish the vertical and horizontal edge of the image and/or text of acard by fitting a virtual line along the edge of the image and/or text(looking down at the surface of the Subject) from the top of the card tothe bottom (vertical image edge) or from the left edge of the imageand/or text to the right edge of the image and/or text (horizontal imageedge) defined by a threshold permitting that virtual line to be fitthrough an array of pixels, to meet a predetermined threshold. Thisprocess of fitting a virtual line may be identical to the process offitting a virtual line on the outermost edge for Vertical and Horizontalcentering Line.

On occasion, an image may extend to the outermost edge of the card. Whenthis occurs, the Horizontal and Vertical centering Edges may beestablished at the outermost edge only. Centering is then measured byidentifying a specific point on the Golden Image that is in the precisecenter (“Centering Point”) of the Golden Image. That Centering Point isisolated in pixels and placed on the Subject. The system 100 may beconfigured to utilize high resolution imaging to determine if theCentering Point from the Golden Image is higher or lower (centering topand bottom) and left or right (centering left and right) on the card.This provides the system 100 the necessary data to calculate in Micronsor Pixels or other increment what percentage the card image isoff-center in any direction and/or that the card may be a possiblealtered or counterfeit card, as well as a contributor to a fingerprintidentification.

When the outermost edge provides a border to the card, image pixelmeasurement or other image processing methods may be employed to measurethe distance between the outer edge of the card and the outer edge ofthe image, both vertically (“Vertical Centering Lines”) and horizontally(“Horizontal Centering Lines”), front and back, as a means ofestablishing the width of all borders surrounding the image and/or textand thereby measuring the centering of the image and/or text on theSubject, front and back.

Pixel measurement or other image processing methods when used to measurethe distance between the outer edge and the peaks and valleys of thecard, create an absolute and unique “fingerprint” for that card, therebypermitting the system 100 to guarantee that if a previously graded cardis re-examined by the system 100 for authentication, such authenticationcan be guaranteed and confirmed.

The edges can also be measured using a binary large objects (“blob”)analysis, as shown in FIGS. 12A-13. Blob analysis employs mathematicalmethods to detect regions in a digital image that differ in properties,such as brightness or color, compared to areas surrounding thoseregions. Informally, a blob is a region of a digital image in which someproperties are constant or vary within a prescribed range of values; allthe points in a blob can be considered in some sense to be similar toeach other. Blob analysis is able to identify, quantify, measureindividual defect and cumulative total defects area and report onSubject defects otherwise not visible even with traditionalmagnification aids.

In one aspect, the computer system 104 utilizes blob analysis incombination with various lighting configurations from above and belowand high angle and low angle lighting precisely located relative to thesurface of the Subject. Blob analysis, when used as a stand-alone toolmeasures light diffusion on the edge of a collectible 116, or on thesurface of a collectible 116, which will identify and assist inmeasuring otherwise imperceptible cracks, creases, dents, fraying, chipsand scratches. Light sources 114, for example LED lighting, willilluminate the defects that are typically undetectable by other means.Blob analysis may gather data relating to this light diffusion toquantify and measure the area in which the diffusion occurs. Blobanalysis may then utilize pre-determined thresholds so that the lightdiffusion may be identified and measured for authentication and gradingpurposes. Blob analysis identifies defects in such high resolution thatmany defects while noted are too small or inconsequential to be ofgrading value. Predetermined thresholds may be utilized to determinewhich collectible 116 data collected by blob analysis will be used tolater authenticate the collectible 116 (“Fingerprint”) for which purposeno defect is too small or inconsequential. These same thresholds may beutilized to determine which defects and data will be used to grade thecollectible 116. When the data for grading purposes is determined, theycan then be applied to create a collectible grade. If any blob analysisdefects are below a size considered in grading and therefore notutilized in the collectible grading scheme, they may nevertheless bestored in the database 130 associated with the collectible image fileand, for example, remain available for identification and authenticationpurposes (“fingerprint”) in the future.

FIGS. 12A-B show examples of blob analysis on edges. FIG. 12A shows anexample of blob analysis of a vertical edge. There are 14 blobs 501totaling 448 Pixels in size. The largest blob is 183 Pixels. The blobsare shown within the box 502.

FIG. 12B shows an example of blob analysis of a horizontal edge. Thereare 11 blobs 501 totaling 234 Pixels. The largest blob measures 44Pixels.

Blob analysis may be combined with other image processing tools toidentify defects on a collectible or card 116. In the card of FIG. 13,angle lighting and blob analysis enables the system 104 to determinethat the upper right corner 701 has at one point in time been slightlybent (no crease was incurred by the bend but the image retains visibleeffect from the bend). This combination of image processing enables thesystem 104 to determine that the bend was in a downward manner. If thebend were in an upward manner, the corner defect would be darker thanthe surface of the card 116. Image processing is used to determine thedegree of defect in any corner of the card 116 by measuring the area ofeach corner that does not precisely conform with the Golden image 117 oris not a ninety-degree corner and quantifying that missing area by itsnumber of nonconforming pixels.

As shown in FIG. 13, the card 116 has a corner which has been bentdownward. The bent corner measures 223 pixels. FIG. 5 illustrates acorner analysis for a card 116 having a corner defect in its upper lefthand corner 901 (from a front viewing perspective). There is one defect902 measuring 858 pixels in area. To the right, the figure shows thesame corner magnified so that the defect may be seen by the naked eye.In this manner, the system 104 determines that the card 116 has aslightly damaged corner—missing 858 pixels from this area. FIG. 10illustrates a corner analysis for a card 116 having a badly damagedcorner. The system 104 identifies an upper left corner that has threedefects. The total area of the three defects is 5,212 pixels. Thelargest of the three defects measures 5,082 pixels. The right-mostfigure panel shows a magnified view of the same card with the upper leftcorner defects are now visible to the naked eye. Note the hanging fibersand the Peaks and Valleys that enable system 104 to “fingerprint” thiscard and authenticate it at a later date as the card originally gradedby the system 104.

A centering algorithm, as shown in FIG. 4, can be used to obtain acentering score, based on several component attributes:

-   -   a. The margin between the edge of the cardstock and the start of        the card image is measured on each of the four sides of the        card: the top/bottom ratio is one attribute, e.g., 63.2/36.8 and        the left-right ratio is a second attribute, e.g., 40/60.    -   b. The alignment of the card image relative to the edges of the        cardstock is measured and distilled into an angle of rotation        for the card image.

An industry-standard mapping of centering-ratios to overallcentering-score is then used to find the overall centering-score for thecard. For example, horizontal centering lines and horizontal centeringedge are determined, and the system 104 can, for example, use up to 100measurement points along the lines measuring the distance between thelines and resultantly any image slope (slant in the printing of theimage on the card) associated with the image on the card. Thiscalculation may be performed on Horizontal Centering Lines and VerticalCentering Lines to determine the width of the border on all sides of theimage of the collectible 116. The system 104 calculation identifies thedegree of off-centeredness of the image of the collectible 116 as wellas the pixel variance on each border between the largest width and thenarrowest width and compares them to the Golden image 117 to confirmthey are defects. Thresholds may be applied and grading defects therebydetermined. Defects outside the grading thresholds may be stored in theimage file in the database 130 for authentication purposes, if needed,at a later date.

FIG. 8 illustrates an example of an image centering analysis accordingto an aspect of the disclosure. The left margin of this Frank Torrebaseball card shown in FIG. 8 is determined to be 42.2414 pixelswide=55.39%; while the right margin is determined to be 34.0168 pixelswide.=44.61%. Therefore, the L/R margin ratio is 55.4/44.6%.

A surface algorithm seeks to give each object card a score based on thecondition of the central surface of the card. Specifically, itdowngrades this score based on, among other defects such as slope, thefollowing card conditions:

-   -   a. Tape, glue, or other materials are affixed to the card 116,        e.g., from prior mounting or accidental contact. In addition,        ink, pencil, or other markings can detract from the overall        grade of a card.    -   b. Scratches, creases or missing layers of the image or        cardstock can also detract from the surface of the card. Removed        staples and pinholes, e.g., from thumbtacks leave punctures in        the cardstock.    -   c. Fading of color of gloss of the image, and/or misprinting        errors also reduce the surface score of an object card.

In order to detect the many different types of surface defects, thesystem 104 compares the images taken under several distinct lightingconditions. These different lighting conditions accentuate the physicalcondition in the collectible 116 in order to detect the many differenttypes of defects that could be present in a collectible. The computersystem 104 compares the images taken under the different lightingconditions, and since the collectible 116 was stationary while theimages were taken resulting in substantially aligned images, alignmentof features from one image to another is made much easier:template-matching can align the images' features within one pixel—and,many times, to a precision greater than that. Even with no externaltemplate (that is, a database image) the difference in images betweenthose lit from one side of the card and the other will reveal creasesand other subtractive defects (pinholes).

In order to detect defects, the card needs to be compared to a templateimage, or in the absence of a template, portions of the card can becompared directly to other areas from the same image or a similar image,e.g., a different card from the same series. Each of the defects found,if any, would reduce the overall surface score for the card throughalgorithms consistent with standard card-grading practice.

FIG. 14 shows an example of a blob analysis combined with other imageprocessing algorithms to identify defects in the card. There are 9measurable areas on a crease line 1101 measuring 838 pixels in totalarea and 394 pixels of area in the largest crease area. The smallestcrease area is 32 pixels. If the threshold for creases were establishedat greater than 32, the smallest of the blob creases would be stored inthe card image file for authentication (“fingerprinting”) purposes at alater date, if needed, but the 32 pixel crease would not be utilized ingrading this card. However the thresholds are set, the blob analysis maybe applied consistently across all cards to give consistent grading ofcards.

The system 100 can be configured to employ Optical character recognition(“OCR”) to read the image and/or text on a collectible 116, and convertit into identifiable and readable text. Thus, the system 100 may use OCRor readable text to identify the collectible 116 in order toautomatically locate its Golden Image 117 in the Golden Image Library orelsewhere in stored images (i.e., Subject Image File). The convertedtext can also be used to compile any other text data on a collectible(e.g. team, town, statistics, date, number, manufacturer, country,names, locations, etc.).

The system 100 may alternatively or also be configured to provide forManual Input of a collectible 116 identifying data should it be a uniquecollectible or be otherwise unknown within the database 130. The system100 may alternatively, or in addition, be configured to use ImageRecognition technology known in the art to identify or match thecollectible 116 with its corresponding Golden Image 117 file.

The system 100 may be configured to analyze the coloring of thecollectible or card 116 and compare it to the Golden Image 117 using RGB(red, green blue) values for its color data. The red, green and bluecoloration of each subject image may be evaluated and described as anaverage value for each color or for all the colors combined. The colordata for each color of a collectible is then compared to the GoldenImage color data to determine how much the colors of the collectiblevary from the colors of the Golden Image. The result is displayed as the“Color Difference” which represents an average difference of the red,green, and blue values and may be stored in computer-accessible computermemory or the database 130.

The system 100 may be configured to accurately measure the thickness ofa card or collectible 116, for example, with a sensitivity of 0.25microns, for the purpose of determining: if the card is counterfeit andon paper stock dissimilar from the Golden image 117; if the card hasbeen “pressed” in an attempt to remove a surface crease; if the card hashad one or more corners pressed in an attempt to “press” lifting ofcorner stock; and, if the card is a previously graded card by the system104. For Example, this measurement may be performed using a ConfocalFiber Displacement Sensor which uses LED lighting (with which theimaging device 106 is equipped), without contact with the card, to moreprecisely measure the thickness than previously available technologysuch as laser triangulation. Thickness measurement may also be performedby other non-contact methods known in the art, such as terahertztime-domain spectroscopy (see Mousavi et al, Simultaneous compositionand thickness measurement of paper using terahertz time-domainspectroscopy, Applied Optics, Vol. 48, Issue 33, pp. 6541-6546 (2009))and multiwavelength THz interferometry (see Nguyen et al., Opticalthickness measurement with multiwavelength THz interferometry, Opticsand Lasers in Engineering, Volume 61, October 2014, Pages 19-22).

The above sections describe how the system arrives at an object-cardscore for each of four large grading criteria: Centering, Corners, Edge,and Surface (including color and gloss). From those four scores,measured on a 0-1000 scale, say, a single overall score for the card iscomputed based on the weighting determined by proprietary algorithms andthat is standard in the card-grading industry. Because the usual outputis provided on a scale from 0 to 10, the system can scale its overallscore to that range or any other range selected.

In order to display its processing results to an output device 122, thesystem 104 generates a grade report, for example in HTML, creating eachscore (and all of their component attributes) as quickly as possible,and swapping the actual results for their placeholders as they becomeavailable. The use of Javascript and its many libraries, e.g., AJAX,makes that swapping possible. By the end of the analysis, the user hasaccess to all of the attributes, scores, raw scores, and overall scorefrom the system. In addition, the images of the card and grade reportfor the card is added to the database 130 in order to improve futurereasoning about identity or quality of scanned or camera-producedimages. In addition, storing the card images in the database 130 enablesthe system 104 to identify individual instances of cards, forauthentication and to facilitate alteration detection and/or counterfeitdetection.

FIGS. 4, 7, 9, 10 and 11 provide examples of card grading reports thatprovide scores of the centering, corners, edges, and surface along withthe overall score card grade in FIG. 3. The Golden image 117 of the card116 is also provided along with the image of the graded card 116. Thecentering analysis and score is displayed in FIG. 7. The score reportfor the edges is displayed in FIG. 9. A score report for the corners ispresented in FIG. 4. A score report for the edges is presented in FIG.11, wherein defect areas on the edges are magnified in a box, as shownin FIG. 11.

With individual instances of scanned cards or collectibles 116 availablein the database 130, the system 104 can use the same techniquesdescribed above to solve—or facilitate—authentication of three types:

-   -   a. By comparing at least one of the: centering, corner, edge,        and/or surface attributes, the system 104 will be able to        distinguish different instances of identical cards 116, e.g.,        two 1963 Topps Mickey Mantle cards. (See FIGS. 15A and 15B).        Only the identical card would match a previously graded image        and stored instance in all of those attributes closely enough to        be considered identical. This contributor to fingerprinting        allows for re-identification of a particular collectible.    -   b. Some of the surface algorithms will be able to flag portions        of a card that have been intentionally altered in order to        artificially raise its grade. For example, in-painting (color        alteration) is a kind of additive surface defect made to cover        over another imperfection in a card.    -   c. The database 130 can store any geometric or other metadata        about each card 116, so that all of the known counterfeit        identifiers can be flagged.

The system 104 can comprise a graphical user interface on the outputdevice 122 that allows a user, through customary mouse motions and otherinput gestures, to specify the locations in a card where the systemwould check for known discrepancies that would signal a possiblecounterfeit.

The computerized system 100 creates an image file of the collectible 116and this file may be stored in the database 130 in remote network-linkedcomputer memory devices, and remain accessible to the computerizedsystem 100 and its customers. The collectible 116 image in the database130 is also a “fingerprint” of the collectible 116. In the images storedat the resolution used by the system 100, the corners and centering areunique and cannot ever be reproduced or counterfeited. The computerizedsystem 100 can measure and capture an image of a corner and/or thecentering (width of image borders horizontal and vertical) in suchdetail that the corner and centering of the image on the collectible orcard 116 could always be confirmed in the future. The computerizedsystem 100 measures the edge of each collectible 116 precisely such thatthe system 100 is able to identify “peaks” and “valleys” on each edge.These peaks and valleys are unique and can never be reproduced orcounterfeited. By retaining a high resolution image of the gradedcollectible 116 a person at any time in the future can send thecollectible 116, or its image via any electronic means, to beauthenticated by the system 100 and confirm that the collectible 116 isthe same collectible 116 as originally analyzed and graded. A person mayalso confirm that the collectible 116 of inquiry is not a counterfeit ofthe original collectible 116.

At least one advantage of the disclosure is that a graded card orcollectible 116 can be authenticated, while the card is either within orremoved from its original grading holder, at any time after the initialgrading. This provides the added security to ensure that the card beingauthenticated or regraded is the identical card that was originallygraded by the disclosure. The disclosure provides a higher securitymeasure over conventional grading companies, which typically issue aserial number to the card they grade, and/or a certification that thecard was graded by them. Conventional grading companies retain adatabase of the serial numbers for the cards they have graded, but donot retain images of the graded card detailing the physical condition ofthe card and/or defects at the time the card was graded (a card“fingerprint”). Cards graded under conventional processes can beresubmitted until a desired high grade is obtained. The high grade isobtained due to different humans examining the card. The disclosure willidentify that a card has been graded and provide a grade that isidentical or consistent with the original grade. The subsequent gradecould be lower than the original grade if the condition of the card haschanged since it was originally graded. As such, the disclosure preventsthe inflation of grades of cards.

Yet another advantage of the disclosure is to further assist the marketplace in discerning whether a collectible 116 is counterfeit or has beenreplaced with another collectible. For example, a card that is not acounterfeit, but is not the identical card that was originally graded.The system 100 may maintain ownership data for each collectible 116 andthis information may be stored in a correlated manner with the“fingerprint” image, for example in a data structure such as thedatabase 130. In one aspect, a person may be granted access to thedatabase 130 and confirm that the owner of the collectible 116 is asrepresented by a third party. This feature permits a buyer of acollectible 116 to confirm that the collectible 116 is authentic andthat the seller is the legitimate owner. With each transfer ofownership, a recorded owner and a buyer together will have access toupdate the ownership record in the database 130.

In one aspect, the computerized system 100 uses a 1,000 point gradingsystem and converts data collected by image processing to a numericscore and a standardized grade. For example, a 1,000 point max scale maybe reduced by thresholds and applied algorithms such that the finalscore is 815. The 815 may be reported at 81.5 or 8.15 and with theapplicable grade for an 815 score (i.e., Perfect, Pristine, Gem Mint,Mint, Mint/Near Mint, Near Mint/Excellent, Excellent/Good,Good/Fair/Poor, etc.). Unlike other grading companies, the computerizedsystem 100 may be configured to provide a grade report comprising adetailed defect report itemizing any deduction in score. The gradereport can also comprise a detailed image report that will show an imageof the collectible 116 with the location of noted defects identified.The grade report may also be configured to provide a provenance reportand authentication report in order to eliminate counterfeiting and fraud(alterations). This 1,000 point grading system also provides anopportunity for collectible 116 owners to differentiate their gradedcollectibles 116 by score and/or grade report. Thus permitting twocollectibles 116 graded with the same standardized grade (Mint/Near Mintfor example) to differentiate their collectibles 116 and more preciselydetermine relative value. Additionally, people who value certain typedefects differently may differentiate between collectibles 116 bothscored the same (815 and 815, for example) but with different defectattributes. For example, because general eye appeal may be an importantcomponent of value for a particular buyer and “beauty” is in the eye ofthe beholder, one collector may value good corners more than centeringor gloss than another does and will be able to discern the gradingdetails to exercise his/her preference.

Aspects of the disclosure may comprise high resolution scanner images orhigh magnification lenses and/or high-resolution digital cameras tocapture images with detail that is imperceptible to the naked eye evenusing hand held magnifiers, as is currently used in conventionalgrading. Precise imaging tools may, for example, be utilized to measurethickness, curves, indents, depth, breadth, size, scratches, dents,creases, color, area, length, etc. Precise location and stability oftools in an enclosed and controlled environment are utilized to assureconsistency of results. Because the human element is removed, grading ofa given collectible 116, when repeated, will provide within known fixedfilters and proprietary algorithms, a statistically valid and similarresult, over and over again. Environmental factors are removed from theprocess such as uncontrolled light, physical movement, distance of lensfrom Subject, angle, type and configuration of lights and variations inthe application of image processing algorithms, as well as fatigue,emotional variance, different eyesight capabilities and different humanweighting of defects from different human graders to assure consistency.The computerized system 100 may utilize many image processing algorithmsto examine all the criteria necessary for grading. The computerizedsystem 100 may be implemented as a system utilizing a comprehensiveexamination and analysis of all grading aspects of a collectible 116 forthe purpose of grading a given collectible 116 in a consistent manner. Aprecise and accurate grade must be able to be similarly reproduced on agiven collectible 116 when such collectible 116 is tested repeatedly. Aprecise and accurate grading system must use grading criteria that arestandardized and consistently applied to all collectibles 116 if it isto provide a basis for comparing one collectible to another when thecollectibles are not similar, such as a 1952 Topps Mickey MantleBaseball card with a 1957 Topps Mickey Mantle baseball card.

There is no grading system in use today that is not manual, i.e., basedon human judgment. These grading systems lead to errors, inconsistentgrades, varying points of grading emphasis by individual graders andre-grading of the same card resulting in different grades. Manualsystems may also provide higher grades given to more “important”customers or larger users of the grading service thus depriving thesmaller customer from playing on a level playing field. Gradingcompanies state publicly that graders do not know the owner of acollectible 116 but this statement neither assures that anon-grader/supervisor does not know the collectible 116 owner's identitynor that the nongrader/supervisor does not have the means to influence agrade. Further, it is equally important that a card grade may beinfluenced as it is that the market believes that it could beinfluenced.

TAG Proof is a card that is identified as virtually perfect and does nothave any defects. Similar in concept to a Proof coin issued by the U.S.Mint, the TAG Proof is issued by the manufacture. TAG will go to themanufacture's printing facilities and grade cards as they are printed.TAG will wear gloves; human hands will not touch the cards. As TAGidentifies cards that receive a perfect grade (Proof) subject topermitted system variance they will be placed in holders and marked as“Proof”. The TAG Proof card can be the standard upon which other cardsof the same type are compared against to determine the grade and/orquality.

Although the present disclosure and its advantages have been describedin detail, it should be understood that various changes, substitutionsand alterations can be made herein without departing from the technologyof the disclosure as defined by the appended claims. For example,relational terms, such as “above” and “below” are used with respect to alight source or a collectible. Of course, if the light source orcollectible is inverted, above becomes below, and vice versa.Additionally, if oriented sideways, above and below may refer to sidesof the light source or collectible. Moreover, the scope of the presentapplication is not intended to be limited to the particularconfigurations of the process, machine, manufacture, composition ofmatter, means, methods and steps described in the specification. As oneof ordinary skill in the art will readily appreciate from thedisclosure, processes, machines, manufacture, compositions of matter,means, methods, or steps, presently existing or later to be developedthat perform substantially the same function or achieve substantiallythe same result as the corresponding configurations described herein maybe utilized according to the present disclosure. Accordingly, theappended claims are intended to include within their scope suchprocesses, machines, manufacture, compositions of matter, means,methods, or steps.

Those of skill would further appreciate that the various illustrativelogical blocks, modules, circuits, and algorithm steps described inconnection with the disclosure herein may be implemented as electronichardware, computer software, or combinations of both. To clearlyillustrate this interchangeability of hardware and software, variousillustrative components, blocks, modules, and steps have been describedabove generally in terms of their functionality. Whether suchfunctionality is implemented as hardware or software depends upon theparticular application and design constraints imposed on the overallsystem. Skilled artisans may implement the described functionality invarying ways for each particular application, but such implementationdecisions should not be interpreted as causing a departure from thescope of the present disclosure.

The various illustrative logical blocks, and modules described inconnection with the disclosure herein may be implemented or performedwith a general-purpose processor, a digital signal processor (DSP), anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA) or other programmable logic device, discrete gate ortransistor logic, discrete hardware components, or any combinationthereof designed to perform the functions described herein. Ageneral-purpose processor may be a microprocessor, but in thealternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, multiple microprocessors, one or moremicroprocessors in conjunction with a DSP core, or any other suchconfiguration.

The steps of a method or algorithm described in connection with thedisclosure may be embodied directly in hardware, in a software moduleexecuted by a processor, or in a combination of the two. A softwaremodule may reside in RAM, flash memory, ROM, EPROM, EEPROM, registers,hard disk, a removable disk, a CD-ROM, solid state storage, or any otherform of storage medium known in the art. An exemplary storage medium iscoupled to the processor such that the processor can read informationfrom, and write information to, the storage medium. In the alternative,the storage medium may be integral to the processor. The processor andthe storage medium may reside in an ASIC. The ASIC may reside in a userterminal. In the alternative, the processor and the storage medium mayreside as discrete components in a user terminal. In yet other aspects,the processor can be remote to the storage medium and accesses thestorage medium through a linked connection.

In one or more exemplary designs, the functions described may beimplemented in hardware, software, firmware, or any combination thereof.If implemented in software, the functions may be stored on ortransmitted over as one or more instructions or code on acomputer-readable medium. Computer-readable media includes both computerstorage media and communication media including any medium thatfacilitates transfer of a computer program from one place to another. Astorage media may be any available media that can be accessed by ageneral purpose or special purpose computer. By way of example, and notlimitation, such computer-readable media can include RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, solid state, or any other medium that can beused to carry or store specified program code means in the form ofinstructions or data structures and that can be accessed by ageneral-purpose or special-purpose computer, or a general-purpose orspecial-purpose processor. Also, any connection is properly termed acomputer-readable medium. For example, if the software is transmittedfrom a website, server, or other remote source using a coaxial cable,fiber optic cable, twisted pair, digital subscriber line (DSL), orwireless technologies such as infrared, radio, and microwave, then thecoaxial cable, fiber optic cable, twisted pair, DSL, or wirelesstechnologies such as infrared, radio, and microwave are included in thedefinition of medium. Disk and disc, as used herein, includes compactdisc (CD), laser disc, optical disc, digital versatile disc (DVD),floppy disk and Blu-ray disc where disks usually reproduce datamagnetically, while discs reproduce data optically with lasers.Combinations of the above should also be included within the scope ofcomputer-readable media.

In the present disclosure, the processor may serve as a structure forcomputer-implemented functions as described herein because thefunction(s) described in one or more aspects of the present disclosureare coextensive with the processor itself. Further, such a processor mayserve as structure for functions that may be achieved by a generalpurpose computer without special programming, because the coextensivefunctions include receiving data, storing data, processing data, etc.Further, the present disclosure are removed from the abstract, and donot merely limit the use of an abstract idea to a particulartechnological environment. The present disclosure expands basic buildingblocks beyond the mere sum of the parts, at least for the reason thatthe present disclosure provides faster, more consistent, and morereliable results than obtainable with current methods and devices.

The previous description of the disclosure is provided to enable anyperson skilled in the art to make or use the disclosure. Variousmodifications to the disclosure will be readily apparent to thoseskilled in the art, and the generic principles defined herein may beapplied to other variations without departing from the spirit or scopeof the disclosure. Thus, the disclosure is not intended to be limited tothe examples and designs described herein but is to be accorded thewidest scope consistent with the principles and novel features disclosedherein.

We claim:
 1. A computerized system for grading a collectible,comprising: a computer system comprising at least one processorcomprising processor-executable computer instructions; wherein saidcomputer system is configured to receive at least one image of saidcollectible; and at least one processing routine applied to said atleast one image by said at least one processor, wherein a grade reportof said collectible is produced based at least on results of said atleast one processing routine.
 2. The computerized system of claim 1,wherein said computer system is configured to access a database, whereinsaid database comprises a datastore of information related to thecollectible, wherein said at least one image is stored on said database.3. The computerized system of claim 2, wherein said datastore ofinformation comprises a collectible identification information relatedto an entity that is a subject of said collectible.
 4. The computerizedsystem of claim 2, wherein said datastore of information comprises data,facts, statistics, figures, and/or the like related to at least oneentity that is a subject of said collectible.
 5. The computerized systemof claim 2, wherein said datastore of information comprises at least onemeasured attribute of said collectible, at least one set of metadata ofsaid collectible, and said at least one image of said collectible. 6.The computerized system of claim 5, wherein said at least one set ofmetadata is associated with one or more characteristics of saidcollectible.
 7. The computerized system of claim 2, wherein saiddatastore of information is configured to be searchable.
 8. Thecomputerized system of claim 2, wherein said datastore of informationcomprises at least one reference image, said at least one referenceimage comprising an image of said collectible without any unintendeddefects, wherein said at least one processor applies said at least oneprocessing routine to said at least one image of said collectible withrespect to said at least one reference image.
 9. The computerized systemof claim 8, wherein said at least one reference image can be created byenhancing said at least one image of said collectible by removingdetectable defects.
 10. The computerized system of claim 8, wherein saidat least one reference image can be a previously graded similarcollectible having the highest graded score as determined by thecomputerized system.
 11. The computerized system of claim 2, whereinsaid computerized system is configured to apply a second processingroutine to said at least one image to produce said grade report in theevent that said datastore of information does not comprise at least onereference image of said collectible.
 12. The computerized system ofclaim 11, wherein said second processing routine comprises at least oneperceptual hash or the like.
 13. The computerized system of claim 1,wherein said at least one processing routine identifies one or moreunique physical characteristics of said collectible, wherein said one ormore unique physical characteristics define a fingerprint of saidcollectible.
 14. The computerized system of claim 13, wherein saidfingerprint can be utilized by said computerized system to determinewhether a subsequent collectible has been previously graded by saidcomputerized system.
 15. The computerized system of claim 1, whereinsaid at least one image of said collectible can be acquired remote fromsaid computer system.
 16. The computerized system of claim 1, whereinsaid at least one image can be acquired by a digital camera, a scanner,a smart phone, or a linked computer.
 17. A computerized system forgrading a collectible, comprising: a computer system comprising at leastone processor comprising processor-executable computer instructions,said computer system configured to receive at least one external signalcomprising at least one image of said collectible; and at least oneprocessing routine applied to the at least one external signal, whereina grade report of said collectible is produced based on the results ofsaid at least one processing routine.
 18. The computerized system ofclaim 17, wherein said at least one external signal further comprises aset of metadata associated with said collectible.
 19. The computerizedsystem of claim 18, wherein said set of metadata was assigned prior tosaid at least one external signal being received by said computersystem.
 20. The computerized system of claim 17, wherein said computersystem is configured to assign a set of metadata to said at least oneimage.
 21. The computerized system of claim 17, wherein a set ofmetadata associated with said at least one image is stored on a databaseaccessible by said computer system.
 22. A method of grading acollectible, comprising: receiving, at a computer system, at least onedigital image of said collectible; assigning a set of metadata to saidat least one digital image, wherein said set of metadata is associatedwith one or more characteristics of said collectible; applying at leastone processing routine to said at least one image; assigning a numericalvalue to results of said at least one processing routine according to apredetermined grading criteria; and producing a grade report based onresults of said at least one image processing routine.
 23. The method ofclaim 22, further comprising: determining whether said collectiblecomprises at least one defect; and providing an indication whether atleast one defect is detected.
 24. The method of claim 23, furthercomprising: identifying said at least one defect of said collectiblewithin said at least one image of said collectible.